Clinicopathological and molecular predictors of [

Disease detection Early breast cancer HER2-positive Predictors [18F]FDG-PET

Journal

European journal of nuclear medicine and molecular imaging
ISSN: 1619-7089
Titre abrégé: Eur J Nucl Med Mol Imaging
Pays: Germany
ID NLM: 101140988

Informations de publication

Date de publication:
08 Apr 2024
Historique:
received: 01 12 2023
accepted: 10 03 2024
medline: 8 4 2024
pubmed: 8 4 2024
entrez: 8 4 2024
Statut: aheadofprint

Résumé

The PHERGain study (NCT03161353) is assessing early metabolic responses to neoadjuvant treatment with trastuzumab-pertuzumab and chemotherapy de-escalation using a [ A total of 500 patients with HER2 + EBC screened in the PHERGain trial with a tumor size > 1.5 cm by magnetic resonance imaging (MRI) were included in the RESPONSE substudy. PET[-] criteria entailed the absence of  ≥ 1 breast lesion with maximum standardized uptake value (SUVmax) ≥ 1.5 × SUVmean liver + 2 standard deviation. Among 75 PET[-] patients screened, 21 with SUVmax levels < 2.5 were randomly selected and matched with 21 PET[+] patients with SUVmax levels ≥ 2.5 based on patient characteristics associated with [ Median SUVmax at baseline was 7.2 (range, 1-39.3). Among all analyzed patients, a higher SUVmax was associated with a higher tumor stage, larger tumor size, lymph node involvement, hormone receptor-negative status, higher HER2 protein expression, increased Ki67 proliferation index, and higher histological grade (p < 0.05). [ These results highlight the clinical, biological, and metabolic heterogeneity of HER2+ breast cancer, which may facilitate the selection of HER2+ EBC patients likely to benefit from [ Clinicaltrials.gov; NCT03161353; registration date: May 15, 2017.

Sections du résumé

BACKGROUND BACKGROUND
The PHERGain study (NCT03161353) is assessing early metabolic responses to neoadjuvant treatment with trastuzumab-pertuzumab and chemotherapy de-escalation using a [
METHODS METHODS
A total of 500 patients with HER2 + EBC screened in the PHERGain trial with a tumor size > 1.5 cm by magnetic resonance imaging (MRI) were included in the RESPONSE substudy. PET[-] criteria entailed the absence of  ≥ 1 breast lesion with maximum standardized uptake value (SUVmax) ≥ 1.5 × SUVmean liver + 2 standard deviation. Among 75 PET[-] patients screened, 21 with SUVmax levels < 2.5 were randomly selected and matched with 21 PET[+] patients with SUVmax levels ≥ 2.5 based on patient characteristics associated with [
RESULTS RESULTS
Median SUVmax at baseline was 7.2 (range, 1-39.3). Among all analyzed patients, a higher SUVmax was associated with a higher tumor stage, larger tumor size, lymph node involvement, hormone receptor-negative status, higher HER2 protein expression, increased Ki67 proliferation index, and higher histological grade (p < 0.05). [
CONCLUSIONS CONCLUSIONS
These results highlight the clinical, biological, and metabolic heterogeneity of HER2+ breast cancer, which may facilitate the selection of HER2+ EBC patients likely to benefit from [
TRIAL REGISTRATION BACKGROUND
Clinicaltrials.gov; NCT03161353; registration date: May 15, 2017.

Identifiants

pubmed: 38587643
doi: 10.1007/s00259-024-06683-0
pii: 10.1007/s00259-024-06683-0
doi:

Banques de données

ClinicalTrials.gov
['NCT03161353']

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : F. Hoffmann-La Roche
ID : SRD-0120112

Informations de copyright

© 2024. The Author(s).

Références

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Auteurs

Antonio Llombart-Cussac (A)

Hospital Arnau de Vilanova, FISABIO, Valencia, Spain. antoniollombart@medsir.org.
Universidad Católica de Valencia, Valencia, Spain. antoniollombart@medsir.org.
Medica Scientia Innovation Research (MEDSIR), Barcelona, Spain. antoniollombart@medsir.org.

Aleix Prat (A)

Hospital Clínic i Provincial de Barcelona, Barcelona, Spain.
University of Barcelona, Barcelona, Spain.
Translational Genomics and Targeted Therapies in Solid Tumors Lab., Barcelona, Spain.

José Manuel Pérez-García (JM)

Medica Scientia Innovation Research (MEDSIR), Barcelona, Spain.
International Breast Cancer Center, Pangea Oncology, QuironSalud Group, Barcelona, Spain.

José Mateos (J)

IEC Barcelona, Barcelona, Spain.

Tomás Pascual (T)

Hospital Clínic i Provincial de Barcelona, Barcelona, Spain.

Santiago Escrivà-de-Romani (S)

Hospital Universitari Vall Hebrón. Vall d'Hebron Institute of Oncology, Barcelona, Spain.

Agostina Stradella (A)

ICO L'Hospitalet, Barcelona, Spain.

Manuel Ruiz-Borrego (M)

Hospital Virgen del Rocío, Seville, Spain.

Begoña Bermejo de Las Heras (BB)

HCU Valencia, INCLIVA, Universidad de Valencia (CIBERONC-ISCIII, Madrid), Valencia, Spain.

Marleen Keyaerts (M)

Vrije Universiteit Brussel, Brussels, Belgium.

Patricia Galvan (P)

Translational Genomics and Targeted Therapies in Solid Tumors Lab., Barcelona, Spain.

Fara Brasó-Maristany (F)

Translational Genomics and Targeted Therapies in Solid Tumors Lab., Barcelona, Spain.

Juan José García-Mosquera (JJ)

Dr. Rosell Oncology Institute (IOR), Dexeus University Hospital, Pangaea Oncology, Quironsalud Group, Barcelona, Spain.

Thomas Guiot (T)

Université Libre de Bruxelles, Hôpital Universitaire de Bruxelles, Institute Jules Bordet, Brussels, Belgium.

María Gion (M)

Hospital Ramón y Cajal, Madrid, Spain.

Miguel Sampayo-Cordero (M)

Medica Scientia Innovation Research (MEDSIR), Barcelona, Spain.

Serena Di Cosimo (S)

Fondazione IRCCS Istituto Nazionale Dei Tumori, Milano, Italy.

Jhudit Pérez-Escuredo (J)

Medica Scientia Innovation Research (MEDSIR), Barcelona, Spain.

Manuel Atienza de Frutos (MA)

Universidad Europea de Madrid, Faculty of Biomedical and Health Sciences, Department of Medicine, Madrid, Spain.

Javier Cortés (J)

Universidad Católica de Valencia, Valencia, Spain.
International Breast Cancer Center, Pangea Oncology, QuironSalud Group, Barcelona, Spain.
Universidad Europea de Madrid, Faculty of Biomedical and Health Sciences, Department of Medicine, Madrid, Spain.

Geraldine Gebhart (G)

Université Libre de Bruxelles, Hôpital Universitaire de Bruxelles, Institute Jules Bordet, Brussels, Belgium.

Classifications MeSH